flume 有三大组件source 、channel和sink，各个组件之间都可以相互组合使用，各组件间耦合度低。使用灵活，方便。
1.多sink
channel 的内容只输出一次，同一个event 如果sink1 输出，sink2 不输出； 最终 sink1+sink2=channel 中的数据。
配置文件如下：
a1.sources = r1
a1.sinks = k1 k2
a1.channels = c1
# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.shell = /bin/bash -c
a1.sources.r1.channels = c1
a1.sources.r1.command = tail -F /opt/apps/logs/tail4.log
# channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#sink1
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = mytopic
a1.sinks.k1.kafka.bootstrap.servers = localhost:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.ki.kafka.producer.compression.type = snappy
#sink2
a1.sinks.k2.type = file_roll
a1.sinks.k2.channel = c1
#a1.sinks.k2.sink.rollInterval=0
a1.sinks.k2.sink.directory = /opt/apps/tmp
- 2.多channel 多sink ，每个sink 输出内容一致
（memory channel 用于kafka操作，实时性高，file channel 用于 sink file 数据安全性高）
（多channel 单 sink 的情况没有举例，个人感觉用处不广泛。）
配置文件如下：
a1.sources = r1
a1.sinks = k1 k2
a1.channels = c1 c2
# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.shell = /bin/bash -c
a1.sources.r1.channels = c1 c2
a1.sources.r1.command = tail -F /opt/apps/logs/tail4.log
#多个channel 的数据相同
a1.sources.r1.selector.type=replicating
# channel1
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#channel2
a1.channels.c2.type = file
a1.channels.c2.checkpointDir = /opt/apps/flume-1.7.0/checkpoint
a1.channels.c2.dataDirs = /opt/apps/flume-1.7.0/data
#sink1
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = mytopic
a1.sinks.k1.kafka.bootstrap.servers = localhost:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.ki.kafka.producer.compression.type = snappy
#sink2
a1.sinks.k2.type = file_roll
a1.sinks.k2.channel = c2
#a1.sinks.k2.sink.rollInterval=0
a1.sinks.k2.sink.directory = /opt/apps/tmp3. 多source 单 channel 单 sink
多个source 可以读取多种信息放在一个channel 然后输出到同一个地方
配置文件如下：
a1.sources = r1 r2
a1.sinks = k1
a1.channels = c1
# source1
a1.sources.r1.type = exec
a1.sources.r1.shell = /bin/bash -c
a1.sources.r1.channels = c1
a1.sources.r1.command = tail -F /opt/apps/logs/tail4.log
# source2
a1.sources.r2.type = exec
a1.sources.r2.shell = /bin/bash -c
a1.sources.r2.channels = c1
a1.sources.r2.command = tail -F /opt/apps/logs/tail2.log
# channel1 in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
#sink1
a1.sinks.k1.channel = c1
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.topic = mytopic
a1.sinks.k1.kafka.bootstrap.servers = localhost:9092
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
a1.sinks.ki.kafka.producer.compression.type = snappyflume 像乐高积木一样可以自己随心所欲将不同的组件进行搭配使用，耦合度低。